Yushi Hu

Artificial Intelligence · 2022–2024

A researcher in the Science corpus: 7 papers; trusts 396 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 292 citations into it; #34,767 of 35,345 by trust here, #9,092 by citations
• Computer Vision and Pattern Recognition — 212 citations into it
• Natural Language Processing — 120 citations into it; #5,590 of 5,688 by trust here, #4,361 by citations
• Multimodal Learning — 98 citations into it
• Evaluation & Benchmarks — 67 citations into it
• Representation & Self-Supervised Learning — 24 citations into it
• Alignment & RLHF — 20 citations into it
• Information Systems — 19 citations into it; #8,609 of 8,771 by trust here, #5,078 by citations

Whom Yushi Hu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Alex Krizhevsky
5. Yoshua Bengio
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Jimmy Ba
10. Christian Szegedy

Who trusts Yushi Hu overall

1. Xingyu Fu
2. Yonatan Bitton
3. Jiasen Lu
4. Zhiqiu Lin
5. Yaofang Liu

Papers from Yushi Hu's perspective

Ordered by how strongly the researchers Yushi Hu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Binding Language Models in Symbolic Languages (2022) — 322 citations
• TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering (2023) — 442 citations
• One Embedder, Any Task: Instruction-Finetuned Text Embeddings (2022) — 475 citations
• Fine-Grained Human Feedback Gives Better Rewards for Language Model Training (2023) — 481 citations
• BLINK: Multimodal Large Language Models Can See but Not Perceive (2024) — 543 citations
• Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models (2024) — 316 citations
• PromptCap: Prompt-Guided Task-Aware Image Captioning (2022) — 142 citations